Lipoproteins include a wide variety of particles found in plasma, serum, whole blood, and lymph, comprising various types and quantities of triglycerides, cholesterol, phospholipids, sphyngolipids, and proteins. These various particles permit the solubilization of otherwise hydrophobic lipid molecules in blood and serve a variety of functions related to lipolysis, lipogenesis, and lipid transport between the gut, liver, muscle tissue and adipose tissue. Inflammation can be associated with many different disease states. See, e.g., Fogelman, When Good Cholesterol Goes Bad, Nature Medicine (2004) 10(9): 902-903, Hima Bindu G et al., Friend Turns Foe: Transformation of Anti-Inflammatory HDL to Proinflammatory HDL during Acute-Phase Response, Cholesterol (2011) 2011: Article ID 274629 (7 pages), the contents of which are hereby incorporated by reference as if recited in full herein. Carbohydrate components of glycoproteins can perform biological functions in protein sorting, immune and receptor recognition, inflammation and other cellular processes. It is believed that inflammation may modulate HDL functionality.
Conventionally, a patient's overall risk of coronary heart disease (CHD) and/or cardiovascular disease (CVD) has been assessed based on measurements of cholesterol content of a patient's LDL and HDL particles, denoted as LDL cholesterol (LDL-C) or HDL cholesterol (HDL-C), rather than the numbers of these particles. These two risk factors are often used to assess a patient's risk, and treatment decisions may be made to reduce the “bad” cholesterol (LDL-C) or increase the “good” cholesterol (HDL-C).
On the other hand, advanced lipoprotein test panels have typically included a total High Density Lipoprotein Particle (HDL-P) measurement (e.g., HDL-P number) and a total Low Density Lipoprotein Particle (LDL-P) measurement (e.g., LDL-P number). The particle numbers represent the concentration in concentration units such as nmol/L. The total HDL-P number may be the sum of the concentration values of each of the sub-groups of HDL-P subclasses, e.g., small, medium and large.
It is believed that LDL-P is a better indicator of LDL-related risk of CHD and CVD relative to LDL-C and/or to guide therapy decisions. However, there are still open questions about the different functions of HDL and how to best evaluate CVD and/or CHD risk associated with a patient's HDL. See, e.g., Kher at el., Cholesterol Efflux Capacity, High-Density Lipoprotein Function, and Athersclerosis, N Engl. J. Med. (2011) 364: 127-135; Navab et al., HDL and cardiovascular disease: atherogenic and atheroprotective mechanisms, Nat. Rev. Cardiol., 8, 222-232 (2011); and Fogelman A, When good cholesterol goes bad, Nat. Med. (2004) 10(9): 902-903, the contents of which are hereby incorporated by reference as if recited in full herein.
The mechanisms by which HDL can be protective or non-protective as associated with a person's risk of developing atherosclerosis or heart disease are complex and multifactorial. See, Farmer et al., Evolving Concepts of the Role of High-Density Lipoprotein in Protection from Athersclerosis, Curr Atheroscler Rep (2011) 13:107-114, and Hima Bindu G et al., Friend Turns Foe: Transformation of Anti-Inflammatory HDL to Proinflammatory HDL during Acute-Phase Response, Cholesterol (2011) 2011: Article ID 274629, 7 pages, the contents of which are hereby incorporated by reference as if recited in full herein.
The Framingham study proposed a relatively lengthy risk model that considers many factors such as age, gender, blood pressure, smoking habits, as well as cholesterol values. The research conducted in the Framingham Offspring Study also defined normative and at-risk population values from subjects in the study. See Wilson et al., Impact of National Guidelines for Cholesterol Risk Factor Screening. The Framingham Offspring Study, JAMA, 1989; 262: 41-44.
There remains a need for evaluations that can better predict or assess a person's cardiovascular risk and/or provide risk parameters that can be used for HDL therapy targets.